It is a common desire to enhance images acquired from imaging devices to improve their image quality. Digital radiographic (x-ray) imaging systems capture images that have digital code values that typically represent either linear or log exposure. Image processing algorithms are employed to convert (or render) the raw capture pixel data into a display or print ready form.
It is common for a digital radiographic imaging system to require that the body part and projection information (exam-type) of the image be known prior to processing the image for display. Often these systems require that the user (e.g. a radiologist or radiographic technologist) manually enter this information into the system. This can be a burden to the user and may impact workflow. In addition, if there is an error in the entry, it can result in a sub-optimal presentation of the image requiring the user to reprocess the image with the correct exam-type information or manually adjust the image processing parameters.
Manually setting the image processing parameters for conventional image processing to achieve a desired appearance can often be a formidable task for radiographic system user. The parameter adjustments are often expressed in image science terms that the user is unfamiliar with and often the adjustment of one parameter can affect the appearance of more than one image quality attribute. To achieve the desired image appearance it often requires iteration and requires the user to be highly trained. Often users will resort to simplified look-up-table adjustments (know to those skilled in the art as window/level) to adjust the appearance of the image. This provides a very limited control and often provides sub-optimal results.
Because defining the image processing parameters on a typical radiographic system is a complicated process, users will settle with a very limited selection of looks for their images. For example, a specific body part and projection may be acquired for multiple diagnostic purposes, but in many radiographic systems the image processing is the same independent of diagnostic purpose.
Accordingly, there exists a need for a method and system that automatically processes an image to a desired visual preference.
The present invention provides a method and system for automatically processes an image to a desired visual preference.